Generate structured task descriptions for GitHub Copilot agents using gh-aw frontmatter conventions.
npx skills add https://github.com/githubnext/gh-aw --skill agentic-chat
Please help me install this Agent Skill. Skill: agentic-chat Source: https://github.com/githubnext/gh-aw/tree/main/skills/agentic-chat Command: npx skills add https://github.com/githubnext/gh-aw --skill agentic-chat
This Skill guides an AI assistant to help users create clear, actionable task descriptions for GitHub Copilot agents, ensuring effective communication and successful execution of automated tasks. It simplifies prompt engineering for complex development tasks.
gh-aw terminology, avoiding ambiguities.Ask the agentic-chat skill to help you create a task description for an AI agent to 'refactor the user authentication flow'.
High-intent search queries and answers about installing and using this skill.
Craft task descriptions using a structured format: Objective, Context, Requirements, Steps, and Constraints. Maintain neutral technical tone, decompose complex problems into clear actionable steps, and use gh-aw frontmatter conventions. This ensures AI agents execute your intent accurately without ambiguity.
Problem decomposition guides AI assistants through multi-stage workflows. Structure the task by defining specific objectives, listing hard requirements, mapping logical steps, and noting constraints. Include pseudo-code where necessary to clarify logic, enabling agents to execute refactoring consistently.
Agentic workflow task descriptions must adhere to gh-aw frontmatter specifications and neutral technical tone. Avoid implementation details; focus on specifications and requirements. This compliance ensures GitHub Copilot agents interpret and execute automation tasks correctly across code, documentation, and issue-tracking contexts.
Yes. Structured task descriptions apply across code refactoring, documentation generation, and issue-tracking automation. Specify objectives, context, requirements, and steps clearly; this enables agents to execute consistent workflows in any development context where gh-aw automation applies.
Specification-focused prompts describe what and why without prescribing how. They state requirements, constraints, and desired outcomes, letting agents choose implementation. This approach produces clearer AI communication, fewer misinterpretations, and more flexible automated workflows than implementation-heavy instructions.
dtsongCreate and refine AI prompts through an interactive interview and analytical checklist.
githubnextCreate GitHub Copilot agent tasks from natural language descriptions via gh agent-task.
ric03uecAutomate GitHub issue implementation workflows with worktrees and project board updates.
Mission42-aiCraft agentic prompts with XML tags and reference templates.